Evidence map›Paper›PMID 40038282›Full record

ArticleNature communications2025

A framework for integrating genomics, microbial traits, and ecosystem biogeochemistry.

Zhen Li, William J Riley, Gianna L Marschmann, Ulas Karaoz, Ian A Shirley, Qiong Wu, Nicholas J Bouskill, Kuang-Yu Chang, Patrick M Crill, Robert F Grant and 9 more

Abstract read
In one paragraph

Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

15 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Review
  7. Metabolic inequality in microbial communities.bioRxiv : the preprint server for biology · 2026
    Article
  8. 16S rRNA sequence captures microbial functional potential.bioRxiv : the preprint server for biology · 2026
    Article
  9. Depth of nutrient uptake by deep-rooted plants is regulated by water availability.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Review
  15. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

19 authors.

Zhen LiClimate and Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.ORCID http://orcid.org/0000-0001-9511-3670
William J RileyClimate and Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA. wjriley@lbl.gov.ORCID http://orcid.org/0000-0002-4615-2304
Gianna L MarschmannClimate and Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.ORCID http://orcid.org/0000-0002-9065-2023
Ulas KaraozClimate and Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.ORCID http://orcid.org/0000-0002-8238-6757
Ian A ShirleyClimate and Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.ORCID http://orcid.org/0000-0002-2229-1414
Qiong WuClimate and Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.
Nicholas J BouskillClimate and Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.ORCID http://orcid.org/0000-0002-6577-8724
Kuang-Yu ChangClimate and Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.ORCID http://orcid.org/0000-0002-7859-5871
Patrick M CrillDepartment of Geological Sciences and Bolin Centre for Climate Research, Stockholm University, Stockholm, Sweden.ORCID http://orcid.org/0000-0003-1110-3059
Robert F GrantDepartment of Renewable Resources, University of Alberta, Edmonton, AB, Canada.ORCID http://orcid.org/0000-0002-8890-6231
Eric KingDepartment of Biology, Consumnes River College, Sacramento, CA, USA.
Scott R SaleskaDepartment of Ecology and Evolutionary Biology, University of Arizona, Tucson, AZ, USA.
Matthew B SullivanDepartment of Microbiology, The Ohio State University, Columbus, OH, USA.ORCID http://orcid.org/0000-0001-8398-8234
Jinyun TangClimate and Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.ORCID http://orcid.org/0000-0002-4792-1259
Ruth K VarnerDepartment of Earth Sciences and Institute for the Study of Earth, Oceans and Space, University of New Hampshire, Durham, NH, USA.ORCID http://orcid.org/0000-0002-3571-6629
Ben J WoodcroftCentre for Microbiome Research, School of Biomedical Sciences, Queensland University of Technology, Translational Research Institute, Woolloongabba, QLD, Australia.ORCID http://orcid.org/0000-0003-0670-7480
Kelly C WrightonDepartment of Soil and Crop Sciences, Colorado State University, Fort Collins, CO, USA.ORCID http://orcid.org/0000-0003-0434-4217
EMERGE Biology Integration Institute Coordinators
Eoin L BrodieClimate and Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.ORCID http://orcid.org/0000-0002-8453-8435

Funding

The impact of bacteriophage therapy on wound infection dynamicsR01AI169865 · NIAID · OHIO STATE UNIVERSITY · PI Daniel J Wozniak · 2022 to 2026
$3.7M
DOE | Office of Science (SC) DE-AC02-05CH11231DOE | Office of Science (SC) (#FP00005182DOE | Office of Science (SC) SCW1746National Science Foundation (NSF) 2022070NIAID NIH HHS R01 AI169865
6 · The paper itself

Abstract

Microbes drive the biogeochemical cycles of earth systems, yet the long-standing goal of linking emerging genomic information, microbial traits, mechanistic ecosystem models, and projections under climate change has remained elusive despite a wealth of emerging genomic information. Here we developed a general genome-to-ecosystem (G2E) framework for integrating genome-inferred microbial kinetic traits into mechanistic models of terrestrial ecosystems and applied it at a well-studied Arctic wetland by benchmarking predictions against observed greenhouse gas emissions. We found variation in genome-inferred microbial kinetic traits resulted in large differences in simulated annual methane emissions, quantitatively demonstrating that the genomically observable variations in microbial capacity are consequential for ecosystem functioning. Applying microbial community-aggregated traits via genome relative-abundance-weighting gave better methane emissions predictions (i.e., up to 54% decrease in bias) compared to ignoring the observed abundances, highlighting the value of combined trait inferences and abundances. This work provides an example of integrating microbial functional trait-based genomics, mechanistic and pragmatic trait parameterizations of diverse microbial metabolisms, and mechanistic ecosystem modeling. The generalizable G2E framework will enable the use of abundant microbial metagenomics data to improve predictions of microbial interactions in many complex systems, including oceanic microbiomes.

Indexed as

EcosystemGenomicsMicrobiotaArctic RegionsBacteriaClimate ChangeGreenhouse GasesMetagenomicsMethaneWetlandsGreenhouse GasesMethane

Identifiers

PMID40038282
PMCPMC11880341

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.